This paper reported a structured literature survey of research in wearable technology for upper-extremity rehabilitation. A keyword based search returned 61 papers related to this topic. Examination of the abstracts of these papers identified 18 articles describing distinct wearable systems aimed at upper extremity rehabilitation. They were classified in three categories depending on their functionality: posture and motion monitoring; monitoring and feedback systems that supported rehabilitation exercises; serious games for rehabilitation training. We characterized the state of the art considering respectively the reported performance of these technologies, availability of clinical evidence, or known clinical applications. Based on the insights from the review study, we proposed a smart rehabilitation garment system for variety of patient groups. The garment integrated with smart textiles and wearable electronics. It presented real-time feedback as a vibration delivered through the garment, visual and audio instructions through Android-hand held device (smartphone or tablet).
[1] Brochard S, Robertson J, Médée B, et al. What's new in new technologies for upper extremity rehabilitation? [J]. Curr Opin Neurol, 2010, 23(6): 683-687.
[2] Bonato P. Advances in wearable technology and applications in physical medicine and rehabilitation [J]. J Neurol Engineering Rehabil, 2005, 2(1): 2.
[3] Park S, Jayaraman S. Enhancing the quality of life through wearable technology [J]. IEEE Eng Med Biol Mag, 2003, 22(3): 41-48.
[4] Bonato P. Advances in wearable technology for rehabilitation [J]. Stud Health Technol Inform, 2009, 145: 145-159.
[5] Brewer BR, McDowell SK, Worthen-Chaudhari LC. Poststroke upper extremity rehabilitation: a review of robotic systems and clinical results [J]. Top Stroke Rehabil, 2014, 14(6): 22-44.
[6] Teng XF, Zhang YT, Poon CC, et al. Wearable medical systems for p-Health [J]. IEEE Rev Biomed Eng, 2008, 1: 62-74.
[7] Pantelopoulos A, Bourbakis NG. A survey on wearable sensor-based systems for health monitoring and prognosis [J]. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 2010, 40(1): 1-12.
[8] Wang Q, Chen W, Markopoulos P. Literature review on wearable systems in upper extremity rehabilitation [C]. 2014 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 2014: 551-555.
[9] Nguyen KD, Chen IM, Luo Z, et al. A wearable sensing system for tracking and monitoring of functional arm movement [J]. IEEE/ASME Trans Mechatron, 2011, 16(2): 213-220.
[10] Lee GX, Low KS, Taher T. Unrestrained measurement of arm motion based on a wearable wireless sensor network [J]. IEEE Trans Instrum Meas, 2010, 59(5): 1309-1317.
[11] Daponte P, De Vito L, Sementa C. A wireless-based home rehabilitation system for monitoring 3D movements [C]. IEEE International Symposium, 2013: 282-287.
[12] Zhou H, Stone T, Hu H, et al. Use of multiple wearable inertial sensors in upper limb motion tracking [J]. Med Eng Phys, 2008, 30(1): 123-133.
[13] Brückner HP, Nowosielski R, Kluge H, et al. Mobile and wireless inertial sensor platform for motion capturing in stroke rehabilitation sessions [C]. 5th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI), 2013: 14-19.
[14] Pan JI, Chung HW, Huang JJ. Intelligent shoulder joint home-based self-rehabilitation monitoring system [J]. Int J Smart Home, 2013, 7(5): 395-404.
[15] Dunne L, Walsh P, Smyth B, et al. A system for wearable monitoring of seated posture in computer users [C]. 4th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2007), 2007: 203-207.
[16] Patel S, Hughes R, Hester T, et al. A novel approach to monitor rehabilitation outcomes in stroke survivors using wearable technology [J]. Proc IEEE, 2010, 98: 450-461.
[17] Bento VF, Cruz VT, Ribeiro DD, et al. The vibratory stimulus as a neurorehabilitation tool for stroke patients: Proof of concept and tolerability test [J]. Neurol Rehabil, 2012, 30: 287-293.
[18] Markopoulos P, Timmermans AAA, Beursgens L, et al. Us'em: The user-centered design of a device for motivating stroke patients to use their impaired arm-hand in daily life activities [C]. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011: 5182-5187.
[19] Bleser G, Steffen D, Weber M, et al. A personalized exercise trainer for the elderly [J]. J Ambient Intell Smart Environ, 2013, 5: 547-562.
[20] Timmermans AAA, Seelen HAM, Geers RPJ, et al. Sensor-based arm skill training in chronic stroke patients: results on treatment outcome, patient motivation, and system usability [J]. IEEE Trans Neural Syst Rehabil Eng, 2010, 18(3): 284-292.
[21] Goodney A, Jung J, Needham S, et al. Dr. Droid: Assisting Stroke Rehabilitation Using Mobile Phones [M]// Mobile Computing, Applications, and Services. Springer Berlin Heidelberg, 2010, 76: 231-242.
[22] Mountain G, Wilson S, Eccleston C, et al. Developing and testing a telerehabilitation system for people following stroke: issues of usability [J]. J Eng Des, 2010: 223-236.
[23] Bonato P. Wearable sensors and systems [J]. IEEE Eng Med Biol Mag, 2010, 29: 25-36.
[24] Patel S, Park H, Bonato P, et al. A review of wearable sensors and systems with application in rehabilitation [J]. J Neurol Engineering Rehabil, 2012, 9: 21.
[25] Luo Z, Lim CK, Yang W, et al. An interactive therapy system for arm and hand rehabilitation [C]. IEEE Conference on Robotics, Automation and Mechatronics, 2010: 9-14.
[26] Alankus G, Lazar A, May M, et al. Towards customizable games for stroke rehabilitation [C]. CHI, 2010: 2113-2122.
[27] Beursgens L, Timmermans A, Markopoulos P. Playful ARM hand training after stroke [C]. CHI'12 Extended Abstracts on Human Factors in Computing Systems, 2012: 2399-2404.
[28] Chee KL, Chen IM, Luo ZQ, et al. A low cost wearable wireless sensing system for upper limb home rehabilitation [C]. IEEE Conference on Robotics, Automation and Mechatronics, 2010: 1-8.
[29] Wang Q, Toeters M, Chen W, et al. Zishi: a Smart Garment for Posture Monitoring [C]. CHI'12 Extended Abstracts on Human Factors in Computing Systems, 2016: 3792-3795.